Noises in randomly sampled sparse signals

Spectral Analysis of Randomly Sampled Signals

Reconstruction of Randomly Sampled Sparse Signals Using an Adaptive Gradient Algorithm

Sparse signals can be recovered from a reduced set of samples by using compressive sensing algorithms. The case when available samples are a random subset of a uniformly or nonuniformly sampled signal is considered in this paper. A recalculation procedure is used to reconstruct the nonuniformly sampled signal. Signal recovery is done using an adaptive gradient-based algorithm in the time domain...

Recovery of Randomly Sampled Signals by Simple Interpolators

T h e mean square error performance of simple polynomial interpolators is analyzed for wide-sense stationary signals subjected to randomly t imed sampling represented by stationary point processes. This performance is expressed in dimensionsless parametric terms, with emphasis on asymptotic error behavior at high dimensionless sampling rates 7. T h e form of the asymptotic error expression, and...

Lyapunov Stability Criteria for Randomly Sampled Systems

This study is concerned with the asymptotic behavior of systems in which random sampling occurs; they are studied by a stochastic Lyapunov function method. The control loops under consideration consist of a random sampler (a sampling device which closes at a set of statistically described times in lieu of periodic intervals), a zero order hold, a linear plant, and a feedback element. Sampled sy...

Control of Randomly Sampled Robotic Systems

This paper studies control problems of sampled data systems which are subject to random sample rate variations and delays. Due to the rapid growth of the use of computers more and more systems are controlled digitally. Complex systems such as space telerobotic systems require the integration of a number of sub-systems at different hierarchical levels. While many sub-systems may run on a single ...